library(ggplot2)
library(gganimate)
## Warning: package 'gganimate' was built under R version 4.3.1
library(tidyverse)
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr 1.1.2 ✔ readr 2.1.4
## ✔ forcats 1.0.0 ✔ stringr 1.5.0
## ✔ lubridate 1.9.2 ✔ tibble 3.2.1
## ✔ purrr 1.0.1 ✔ tidyr 1.3.0
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
library(here)
## here() starts at D:/RK/UNSW/Data Visualisation/DATA5002/Project
library(gifski)
## Warning: package 'gifski' was built under R version 4.3.1
library(forcats)
library(animation)
## Warning: package 'animation' was built under R version 4.3.1
library(plotly)
## Warning: package 'plotly' was built under R version 4.3.1
##
## Attaching package: 'plotly'
##
## The following object is masked from 'package:ggplot2':
##
## last_plot
##
## The following object is masked from 'package:stats':
##
## filter
##
## The following object is masked from 'package:graphics':
##
## layout
library(highcharter)
## Warning: package 'highcharter' was built under R version 4.3.1
## Registered S3 method overwritten by 'quantmod':
## method from
## as.zoo.data.frame zoo
library(dplyr)
df <- read.csv(here("Data", "import_export_years.csv"))
head(df)
## year import_export crude_oil lpg ms naphtha atf sko hsd ldo
## 1 1998 import 39808 1722 251 2407 0 7065 10231 0
## 2 1999 import 57805 1587 0 1917 0 6312 5006 0
## 3 2000 import 74097 853 0 3165 0 1918 0 0
## 4 2001 import 78706 659 0 3308 0 391 31 0
## 5 2002 import 81989 1073 0 2784 0 698 106 0
## 6 2003 import 90434 1708 0 2371 0 804 100 0
## lobs_lube_oil fuel_oil bitumen others total
## 1 396 1696 0 3 63579
## 2 407 1377 0 1 74412
## 3 255 1728 0 1348 83364
## 4 326 1977 9 308 85715
## 5 340 2220 0 7 89217
## 6 612 1728 6 672 98435
# Split the data into import and export
import_data <- subset(df, import_export == 'import')
export_data <- subset(df, import_export == 'export')
# Calculate total import excluding crude oil
import_data_no_crude <- import_data
import_data_no_crude$total <- import_data_no_crude$total - import_data_no_crude$crude_oil
import_data_no_crude <- subset(import_data_no_crude, select = -crude_oil)
plt <- ggplot() +
geom_line(data = import_data, aes(x = year, y = total, color = 'Import (Including Crude Oil)', linetype = 'Import (Including Crude Oil)')) +
geom_point(data = import_data, aes(x = year, y = total)) +
geom_line(data = import_data_no_crude, aes(x = year, y = total, color = 'Import (Excluding Crude Oil)', linetype = 'Import (Excluding Crude Oil)')) +
geom_point(data = import_data_no_crude, aes(x = year, y = total)) +
geom_line(data = export_data, aes(x = year, y = total, color = 'Export', linetype = 'Export')) +
geom_point(data = export_data, aes(x = year, y = total)) +
scale_color_manual(values = c('Import (Including Crude Oil)' = 'blue', 'Import (Excluding Crude Oil)' = 'blue', 'Export' = 'red'),
name = "Type",
breaks = c('Import (Including Crude Oil)', 'Import (Excluding Crude Oil)', 'Export'),
labels = c('Import (Including Crude Oil)', 'Import (Excluding Crude Oil)', 'Export')) +
scale_linetype_manual(values = c('Import (Including Crude Oil)' = "solid", 'Import (Excluding Crude Oil)' = "dashed", 'Export' = "solid"),
name = "Type",
breaks = c('Import (Including Crude Oil)', 'Import (Excluding Crude Oil)', 'Export'),
labels = c('Import (Including Crude Oil)', 'Import (Excluding Crude Oil)', 'Export')) +
scale_x_continuous(breaks = seq(min(import_data$year), max(import_data$year), by = 1)) +
scale_y_continuous(n.breaks = 20) +
labs(title = "Comparison of Imports (with and without Crude Oil) and Exports Over the Years",
x = "Year",
y = "Total Quantity") +
theme_bw() +
theme(legend.title = element_blank(),
legend.position = c(0.9, 0.5),
legend.justification = c(0.5, 0.5),
legend.background = element_rect(fill="white",
size=0.5, linetype="solid",
colour ="black"))
## Warning: The `size` argument of `element_rect()` is deprecated as of ggplot2 3.4.0.
## ℹ Please use the `linewidth` argument instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
plot(plt)
fig <- plot_ly() %>%
add_trace(data = import_data, x = ~year, y = ~total, name = 'Import (Including Crude Oil)', type = 'scatter', mode = 'lines+markers', line = list(color = 'blue')) %>%
add_trace(data = import_data_no_crude, x = ~year, y = ~total, name = 'Import (Excluding Crude Oil)', type = 'scatter', mode = 'lines+markers', line = list(color = 'blue', dash = 'dash')) %>%
add_trace(data = export_data, x = ~year, y = ~total, name = 'Export', type = 'scatter', mode = 'lines+markers', line = list(color = 'red')) %>%
layout(title = "Comparison of Imports (with and without Crude Oil) and Exports Over the Years",
xaxis = list(title = "Year"),
yaxis = list(title = "Total Quantity in '000 Metric Tons"))
fig
data_subset <- import_data
data_subset <- data_subset %>%
filter(year == 1999) %>%
select(-year, -import_export, -total) %>%
gather(key = "Product", value = "Quantity")
data_subset
## Product Quantity
## 1 crude_oil 57805
## 2 lpg 1587
## 3 ms 0
## 4 naphtha 1917
## 5 atf 0
## 6 sko 6312
## 7 hsd 5006
## 8 ldo 0
## 9 lobs_lube_oil 407
## 10 fuel_oil 1377
## 11 bitumen 0
## 12 others 1
plot_ly(data_subset, labels = ~Product, values = ~Quantity, type = 'pie') %>%
layout(title = paste("Product Composition in", 1999))
sun <- read.csv(here("Data","import_export_months.csv"))
sun
## year months import_export crude_oil lpg ms naphtha atf sko hsd ldo
## 1 2011 January import 15737 419 20 153 0 129 508 0
## 2 2011 February import 13784 469 0 133 0 141 40 0
## 3 2011 March import 13935 482 215 162 0 111 192 0
## 4 2011 April import 13750 495 135 227 0 110 0 0
## 5 2011 May import 14264 428 108 122 0 73 16 0
## 6 2011 June import 12990 504 36 202 0 0 1 0
## 7 2011 July import 12463 453 140 182 0 0 5 0
## 8 2011 August import 14850 447 0 274 0 0 2 0
## 9 2011 September import 13933 475 0 240 0 0 22 0
## 10 2011 October import 17017 512 0 111 0 0 207 0
## 11 2011 November import 13719 514 0 108 0 0 62 0
## 12 2011 December import 15289 592 0 175 0 0 4 0
## 13 2012 January import 14809 655 0 138 0 0 133 0
## 14 2012 February import 15627 628 0 173 0 0 109 0
## 15 2012 March import 14817 459 0 179 0 0 61 0
## 16 2012 April import 14594 526 57 187 0 0 132 0
## 17 2012 May import 15045 528 90 190 0 0 63 0
## 18 2012 June import 15236 592 0 188 0 0 2 0
## 19 2012 July import 16503 508 0 85 0 0 1 0
## 20 2012 August import 15495 509 0 214 0 0 2 0
## 21 2012 September import 16021 533 0 112 0 0 8 0
## 22 2012 October import 18345 448 0 95 0 0 8 0
## 23 2012 November import 13366 383 0 120 0 0 5 0
## 24 2012 December import 14936 531 0 81 0 0 5 0
## 25 2013 January import 16408 520 0 66 0 0 6 0
## 26 2013 February import 17181 601 15 66 0 0 17 0
## 27 2013 March import 14310 345 115 125 0 0 0 0
## 28 2013 April import 16353 400 76 95 0 0 1 0
## 29 2013 May import 17573 553 0 100 0 0 3 0
## 30 2013 June import 15082 573 0 156 0 0 1 0
## 31 2013 July import 15361 643 29 73 0 0 3 0
## 32 2013 August import 14614 352 0 108 0 0 29 0
## 33 2013 September import 15822 666 0 93 0 0 4 0
## 34 2013 October import 15503 713 0 66 0 0 2 0
## 35 2013 November import 16515 651 0 56 0 0 7 0
## 36 2013 December import 14516 551 0 17 0 0 5 0
## 37 2014 January import 16902 657 0 46 10 0 0 0
## 38 2014 February import 14905 633 0 66 5 30 5 0
## 39 2014 March import 16211 564 61 69 0 0 2 0
## 40 2014 April import 14222 711 143 72 5 0 51 0
## 41 2014 May import 15990 624 50 99 14 0 1 0
## 42 2014 June import 15989 758 20 62 21 0 6 0
## 43 2014 July import 16193 721 38 0 14 0 10 0
## 44 2014 August import 15005 651 16 23 5 0 8 0
## 45 2014 September import 16820 816 0 47 14 0 10 0
## 46 2014 October import 17715 711 0 86 19 0 3 0
## 47 2014 November import 12993 623 0 137 11 0 10 0
## 48 2014 December import 16489 843 44 327 20 0 18 0
## 49 2015 January import 15535 685 120 152 19 35 1 0
## 50 2015 February import 17454 809 154 364 6 0 0 0
## 51 2015 March import 15619 653 170 347 55 6 10 0
## 52 2015 April import 17732 696 133 354 25 0 2 0
## 53 2015 May import 17235 996 38 296 24 0 1 0
## 54 2015 June import 15787 663 51 165 20 0 1 0
## 55 2015 July import 15568 710 143 242 20 0 7 0
## 56 2015 August import 16636 724 33 122 27 0 10 0
## 57 2015 September import 17726 785 98 205 26 0 10 0
## 58 2015 October import 18129 803 53 230 6 0 2 0
## 59 2015 November import 16882 684 0 205 20 0 72 0
## 60 2015 December import 18546 750 20 248 36 0 62 0
## 61 2016 January import 17960 809 74 326 23 0 503 0
## 62 2016 February import 17527 857 157 219 28 0 222 0
## 63 2016 March import 17630 796 38 238 33 0 3 0
## 64 2016 April import 17214 811 0 269 27 0 1 0
## 65 2016 May import 18811 746 90 249 25 0 0 0
## 66 2016 June import 17762 798 84 238 43 0 0 0
## 67 2016 July import 18153 1005 0 215 7 0 5 0
## 68 2016 August import 18756 1021 33 252 34 0 3 0
## 69 2016 September import 18006 1119 0 237 50 0 101 0
## 70 2016 October import 17446 901 0 91 29 0 163 0
## 71 2016 November import 16455 1000 0 209 32 0 5 0
## 72 2016 December import 18212 1235 0 235 7 0 0 0
## 73 2017 January import 18127 906 0 74 29 0 15 0
## 74 2017 February import 17903 752 0 103 23 0 444 0
## 75 2017 March import 17666 618 36 68 25 0 459 0
## 76 2017 April import 17320 934 137 166 22 0 313 0
## 77 2017 May import 18113 1105 0 168 24 0 12 0
## 78 2017 June import 17644 872 0 185 25 0 1 0
## 79 2017 July import 19029 1201 0 234 26 0 3 0
## 80 2017 August import 19191 1233 0 117 34 0 18 0
## 81 2017 September import 19339 1130 0 184 13 0 6 0
## 82 2017 October import 20066 988 0 365 37 0 11 0
## 83 2017 November import 17631 728 0 305 12 0 7 0
## 84 2017 December import 18404 913 0 243 30 0 72 0
## 85 2018 January import 17280 863 0 332 37 0 72 0
## 86 2018 February import 19963 867 164 124 7 0 115 0
## 87 2018 March import 19477 1099 0 199 15 0 6 0
## 88 2018 April import 19583 1083 0 161 30 0 2 0
## 89 2018 May import 18639 1230 37 155 38 0 4 0
## 90 2018 June import 17924 1174 44 160 37 0 2 0
## 91 2018 July import 21102 999 36 242 41 0 19 0
## 92 2018 August import 17014 1028 37 232 21 0 8 0
## 93 2018 September import 19543 1222 37 179 22 0 7 0
## 94 2018 October import 19682 1066 66 52 6 0 71 0
## 95 2018 November import 17114 1213 101 178 0 0 171 0
## 96 2018 December import 19176 1392 148 68 5 0 79 0
## 97 2019 January import 19712 1262 119 119 65 0 135 0
## 98 2019 February import 18869 1037 125 122 0 0 201 0
## 99 2019 March import 16866 958 183 70 0 0 443 0
## 100 2019 April import 19411 857 245 203 0 0 115 0
## 101 2019 May import 19787 1220 174 203 0 0 46 0
## 102 2019 June import 16821 1573 409 259 0 0 140 0
## 103 2019 July import 19303 1413 193 118 0 0 70 0
## 104 2019 August import 19171 1302 138 100 0 0 11 0
## 105 2019 September import 18714 1227 226 135 0 0 507 0
## 106 2019 October import 20138 1411 198 177 0 0 699 0
## 107 2019 November import 18647 1330 61 65 0 0 278 0
## 108 2019 December import 19515 1218 74 90 0 0 148 0
## 109 2020 January import 16553 1358 0 26 0 0 34 0
## 110 2020 February import 14607 1487 0 44 0 0 37 0
## 111 2020 March import 13677 1218 35 176 0 0 70 0
## 112 2020 April import 12335 986 38 157 0 2 136 0
## 113 2020 May import 16859 1228 35 124 0 0 4 0
## 114 2020 June import 15180 1638 75 86 0 0 2 0
## 115 2020 July import 15381 1426 131 154 0 0 14 0
## 116 2020 August import 18290 1394 155 169 0 0 3 0
## 117 2020 September import 20489 1503 544 82 0 0 246 0
## 118 2020 October import 19594 1363 124 48 0 0 73 0
## 119 2020 November import 15235 1521 82 104 0 0 18 0
## 120 2020 December import 18261 1355 133 29 0 0 9 0
## 121 2021 January import 18256 1043 74 39 0 0 3 0
## 122 2021 February import 17259 1046 0 35 0 0 4 0
## 123 2021 March import 15905 1389 0 37 0 0 1 0
## 124 2021 April import 15021 1403 0 0 0 0 1 0
## 125 2021 May import 17387 1695 0 0 0 0 4 0
## 126 2021 June import 17608 1563 153 0 0 0 6 0
## 127 2021 July import 17084 1599 412 0 0 0 2 0
## 128 2021 August import 18340 1581 31 17 0 0 6 0
## 129 2021 September import 19648 1650 0 0 0 0 4 0
## 130 2021 October import 19254 1388 0 0 0 0 3 0
## 131 2021 November import 17589 1249 0 0 0 0 5 0
## 132 2021 December import 19031 1438 0 110 0 0 5 0
## 133 2022 January import 21626 1605 0 35 0 0 3 0
## 134 2022 February import 19644 1363 30 30 0 0 9 0
## 135 2022 March import 19441 1264 127 2 0 0 115 0
## 136 2022 April import 20624 1417 63 145 0 0 146 0
## 137 2022 May import 17637 1574 0 90 0 0 8 0
## 138 2022 June import 16772 1448 190 76 0 0 2 0
## 139 2022 July import 18123 1374 327 135 0 0 10 0
## 140 2022 August import 19003 1778 211 28 0 0 7 0
## 141 2022 September import 19618 1718 120 88 0 0 12 0
## 142 2022 October import 20229 1709 0 41 0 0 5 0
## 143 2022 November import 19285 1647 0 128 0 0 10 0
## 144 2022 December import 20729 1410 0 98 0 0 4 0
## 145 2011 January export 0 13 1184 870 295 2 1391 9
## 146 2011 February export 0 16 1476 800 337 4 2164 9
## 147 2011 March export 0 13 1359 818 436 2 1587 6
## 148 2011 April export 0 12 1144 977 418 3 1637 9
## 149 2011 May export 0 10 1076 998 456 2 1721 9
## 150 2011 June export 0 16 1295 752 461 3 1916 8
## 151 2011 July export 0 15 886 635 521 2 2079 9
## 152 2011 August export 0 16 1052 1025 429 2 1731 0
## 153 2011 September export 0 15 1422 780 411 3 1705 8
## 154 2011 October export 0 12 1089 775 307 4 1262 0
## 155 2011 November export 0 18 1010 842 245 4 1122 8
## 156 2011 December export 0 17 1528 866 245 4 2092 9
## 157 2012 January export 0 17 1231 647 299 2 1331 9
## 158 2012 February export 0 17 1318 638 328 3 1614 0
## 159 2012 March export 0 13 1479 699 246 3 1717 0
## 160 2012 April export 0 19 1310 680 267 3 1611 0
## 161 2012 May export 0 13 1379 756 253 2 1562 0
## 162 2012 June export 0 15 1527 536 392 2 1795 0
## 163 2012 July export 0 18 1514 816 455 2 2637 0
## 164 2012 August export 0 18 1295 924 625 1 2005 0
## 165 2012 September export 0 19 1419 857 490 2 2546 0
## 166 2012 October export 0 19 1436 734 426 2 1929 0
## 167 2012 November export 0 16 1075 656 414 2 1517 0
## 168 2012 December export 0 17 1675 706 467 1 2200 0
## 169 2013 January export 0 19 1211 623 551 1 1621 0
## 170 2013 February export 0 17 1403 739 542 1 1813 0
## 171 2013 March export 0 17 1489 676 336 1 1813 0
## 172 2013 April export 0 18 1242 763 415 1 2358 0
## 173 2013 May export 0 21 1377 832 440 1 2410 0
## 174 2013 June export 0 18 1305 679 559 1 3371 0
## 175 2013 July export 0 15 1222 794 536 1 2357 8
## 176 2013 August export 0 17 1138 586 525 1 2028 8
## 177 2013 September export 0 20 1301 707 504 1 2580 7
## 178 2013 October export 0 23 1013 625 380 2 1562 8
## 179 2013 November export 0 21 1009 614 454 2 2056 0
## 180 2013 December export 0 22 1536 682 503 1 2498 0
## 181 2014 January export 0 21 1200 540 234 1 1738 0
## 182 2014 February export 0 21 1459 522 397 1 2006 6
## 183 2014 March export 0 17 1404 685 333 1 2156 0
## 184 2014 April export 0 20 1241 581 401 1 1354 0
## 185 2014 May export 0 16 1435 572 307 1 1870 0
## 186 2014 June export 0 21 1276 709 614 1 2814 0
## 187 2014 July export 0 18 1391 540 516 1 2797 0
## 188 2014 August export 0 20 1311 756 559 1 2627 0
## 189 2014 September export 0 19 1667 572 603 1 2277 0
## 190 2014 October export 0 26 1352 649 502 2 1975 0
## 191 2014 November export 0 26 1246 404 492 2 2130 0
## 192 2014 December export 0 28 1067 480 563 2 1815 0
## 193 2015 January export 0 24 935 576 153 1 1366 0
## 194 2015 February export 0 19 1341 492 260 1 1495 0
## 195 2015 March export 0 20 1286 614 377 1 1809 0
## 196 2015 April export 0 22 1357 683 501 1 2181 0
## 197 2015 May export 0 19 1537 656 589 1 2432 0
## 198 2015 June export 0 13 1331 552 669 1 2129 0
## 199 2015 July export 0 6 1509 358 300 0 1778 0
## 200 2015 August export 0 5 1438 546 460 0 2264 0
## 201 2015 September export 0 7 1493 698 386 1 1784 0
## 202 2015 October export 0 12 1500 581 693 1 2375 0
## 203 2015 November export 0 17 1573 710 579 1 2353 0
## 204 2015 December export 0 30 1517 649 718 1 2069 0
## 205 2016 January export 0 27 1368 494 674 2 2061 0
## 206 2016 February export 0 29 1561 593 598 1 1437 0
## 207 2016 March export 0 30 1491 602 643 1 2248 0
## 208 2016 April export 0 25 1365 667 496 1 2368 0
## 209 2016 May export 0 22 1160 925 668 1 2848 0
## 210 2016 June export 0 21 1242 926 535 1 2809 0
## 211 2016 July export 0 25 1258 745 622 1 2708 0
## 212 2016 August export 0 24 1102 690 562 1 2417 20
## 213 2016 September export 0 30 1014 834 702 1 2200 0
## 214 2016 October export 0 28 1035 802 537 1 1824 40
## 215 2016 November export 0 26 1204 530 492 1 1751 46
## 216 2016 December export 0 30 1617 918 742 1 2631 45
## 217 2017 January export 0 29 1095 749 562 1 2244 0
## 218 2017 February export 0 29 1333 696 482 1 1956 5
## 219 2017 March export 0 27 1208 767 570 2 2036 0
## 220 2017 April export 0 26 1260 917 540 2 2145 4
## 221 2017 May export 0 26 1060 628 573 1 2793 0
## 222 2017 June export 0 31 1152 642 578 1 3040 0
## 223 2017 July export 0 30 996 851 647 1 2946 4
## 224 2017 August export 0 34 1137 749 558 2 2607 4
## 225 2017 September export 0 32 1167 658 685 1 2895 0
## 226 2017 October export 0 35 1195 761 640 1 2704 0
## 227 2017 November export 0 26 1063 824 621 1 2312 0
## 228 2017 December export 0 35 1371 710 725 1 2039 0
## 229 2018 January export 0 29 915 530 492 1 1555 0
## 230 2018 February export 0 34 1148 542 547 2 1988 0
## 231 2018 March export 0 34 1206 635 730 2 2447 0
## 232 2018 April export 0 34 1047 621 653 2 2482 0
## 233 2018 May export 0 32 840 683 611 2 2844 0
## 234 2018 June export 0 33 1168 762 651 1 2813 0
## 235 2018 July export 0 34 1176 563 598 2 2741 33
## 236 2018 August export 0 29 1110 661 611 1 2311 66
## 237 2018 September export 0 41 1047 625 647 1 2274 0
## 238 2018 October export 0 40 1044 456 606 2 1837 0
## 239 2018 November export 0 36 980 428 496 2 1895 0
## 240 2018 December export 0 41 1203 459 745 2 2648 0
## 241 2019 January export 0 38 1002 615 554 2 2017 0
## 242 2019 February export 0 36 1377 974 473 2 2101 0
## 243 2019 March export 0 34 841 548 634 2 2220 0
## 244 2019 April export 0 38 1156 401 484 2 2614 0
## 245 2019 May export 0 32 904 681 544 2 2357 0
## 246 2019 June export 0 40 1133 780 720 2 3322 0
## 247 2019 July export 0 37 994 880 618 1 3119 0
## 248 2019 August export 0 42 993 736 714 2 3270 0
## 249 2019 September export 0 42 1329 973 656 21 3143 0
## 250 2019 October export 0 39 813 787 497 59 2141 0
## 251 2019 November export 0 41 1027 701 525 21 2390 0
## 252 2019 December export 0 45 1141 820 488 61 2958 0
## 253 2020 January export 0 35 932 683 439 0 3404 0
## 254 2020 February export 0 32 1108 642 304 0 2786 0
## 255 2020 March export 0 32 985 440 255 1 2094 0
## 256 2020 April export 0 31 1012 299 225 2 2058 0
## 257 2020 May export 0 34 874 547 141 1 2790 0
## 258 2020 June export 0 39 984 609 267 1 2673 0
## 259 2020 July export 0 36 797 284 176 2 2373 0
## 260 2020 August export 0 39 895 442 273 2 2244 0
## 261 2020 September export 0 41 954 611 314 2 2653 0
## 262 2020 October export 0 46 890 599 304 2 2324 0
## 263 2020 November export 0 41 884 553 433 1 2109 0
## 264 2020 December export 0 47 1290 801 413 2 3069 0
## 265 2021 January export 0 42 934 458 270 1 1880 0
## 266 2021 February export 0 46 1334 499 418 1 2945 0
## 267 2021 March export 0 36 1146 608 493 2 2834 0
## 268 2021 April export 0 31 1002 477 336 1 2259 0
## 269 2021 May export 0 43 903 635 324 1 2603 0
## 270 2021 June export 0 45 851 656 292 1 2795 0
## 271 2021 July export 0 44 1005 551 453 1 2897 0
## 272 2021 August export 0 46 1035 595 552 1 2781 0
## 273 2021 September export 0 50 1374 642 569 1 3057 0
## 274 2021 October export 0 49 1082 511 448 1 2578 0
## 275 2021 November export 0 45 1217 438 414 1 2415 0
## 276 2021 December export 0 37 1600 791 617 1 3365 0
## 277 2022 January export 0 47 1402 611 350 2 2698 0
## 278 2022 February export 0 47 1157 556 448 1 3063 0
## 279 2022 March export 0 50 1162 815 591 1 2456 0
## 280 2022 April export 0 41 1109 355 583 1 2188 0
## 281 2022 May export 0 39 1018 414 745 0 2365 0
## 282 2022 June export 0 40 671 468 689 1 2689 0
## 283 2022 July export 0 43 500 372 639 1 2062 0
## 284 2022 August export 0 41 842 423 591 1 1979 0
## 285 2022 September export 0 44 1242 441 624 1 2413 0
## 286 2022 October export 0 47 1165 333 568 1 1991 0
## 287 2022 November export 0 42 1379 416 650 1 2150 0
## 288 2022 December export 0 51 1470 511 786 1 2482 0
## lobs_lube_oil fuel_oil bitumen petcoke others total
## 1 116 95 7 0 256 17440
## 2 101 21 9 0 281 14979
## 3 105 60 2 0 293 15557
## 4 82 141 5 0 214 15159
## 5 150 183 1 0 241 15586
## 6 133 159 2 0 233 14260
## 7 94 56 1 0 141 13535
## 8 165 137 5 0 344 16224
## 9 131 81 6 0 175 15063
## 10 128 10 3 0 264 18252
## 11 107 171 15 0 240 14936
## 12 123 90 22 0 295 16590
## 13 142 127 7 0 358 16369
## 14 183 63 14 0 334 17131
## 15 144 50 3 0 301 16014
## 16 121 85 4 0 336 16042
## 17 259 52 1 0 570 16798
## 18 171 95 3 0 356 16643
## 19 144 63 8 0 370 17682
## 20 262 88 13 0 375 16958
## 21 101 78 8 0 375 17236
## 22 157 123 5 0 451 19632
## 23 147 113 16 0 322 14472
## 24 146 101 20 0 355 16175
## 25 147 108 25 0 312 17592
## 26 212 60 32 0 467 18651
## 27 140 48 7 0 262 15352
## 28 185 182 7 0 470 17769
## 29 151 147 2 0 441 18970
## 30 103 121 5 0 589 16630
## 31 188 168 11 0 471 16947
## 32 121 40 21 0 414 15699
## 33 230 122 22 0 272 17231
## 34 269 66 20 0 519 17158
## 35 186 96 63 0 436 18010
## 36 158 175 32 0 476 15930
## 37 273 159 36 0 422 18505
## 38 365 124 39 0 491 16663
## 39 111 126 31 0 662 17837
## 40 150 20 16 0 628 16018
## 41 237 106 26 0 646 17793
## 42 136 76 21 0 866 17955
## 43 171 12 30 0 503 17692
## 44 144 61 56 0 659 16628
## 45 129 30 64 0 784 18714
## 46 100 87 52 0 635 19408
## 47 151 53 63 0 772 14813
## 48 180 50 84 0 654 18709
## 49 205 36 91 0 672 17551
## 50 162 49 95 0 959 20052
## 51 195 273 84 0 674 18086
## 52 182 48 50 0 916 20138
## 53 173 50 37 0 974 19824
## 54 191 116 36 0 1092 18122
## 55 150 78 98 0 1043 18059
## 56 209 64 73 0 872 18770
## 57 186 45 93 0 749 19923
## 58 201 270 62 0 1306 21062
## 59 199 30 49 0 1314 19455
## 60 210 111 111 0 1164 21258
## 61 189 80 120 0 1162 21246
## 62 178 96 145 0 1270 20699
## 63 222 89 79 0 1756 20884
## 64 229 79 24 0 1542 20196
## 65 154 27 26 0 2250 22378
## 66 134 135 25 0 1517 20736
## 67 180 79 87 0 1412 21143
## 68 184 70 70 0 1095 21518
## 69 177 84 89 0 956 20819
## 70 175 43 86 0 1193 20127
## 71 169 58 97 0 1021 19046
## 72 140 85 103 0 1412 21429
## 73 210 85 77 0 1358 20881
## 74 179 166 127 0 1362 21059
## 75 192 45 43 0 1334 20486
## 76 174 99 25 0 1527 20717
## 77 141 43 50 0 1689 21345
## 78 195 58 59 0 1055 20094
## 79 222 116 65 0 1420 22316
## 80 221 93 71 0 1050 22028
## 81 216 67 106 0 1577 22638
## 82 238 106 88 0 1057 22956
## 83 298 143 122 0 836 20082
## 84 254 193 115 0 1068 21292
## 85 111 301 104 0 1080 20180
## 86 201 127 92 0 898 22558
## 87 226 195 59 0 1069 22345
## 88 185 164 46 0 897 22151
## 89 217 78 37 0 881 21316
## 90 162 55 54 0 606 20218
## 91 248 50 56 0 414 23207
## 92 214 36 56 0 628 19274
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sun_import <- subset(sun, import_export == "import")
sun_import <- sun_import %>%
select(-total)
t <- pivot_longer(sun_import, cols = c(crude_oil:others), names_to = "Product", values_to = "Quantity")
t
## # A tibble: 1,872 × 5
## year months import_export Product Quantity
## <int> <chr> <chr> <chr> <int>
## 1 2011 January import crude_oil 15737
## 2 2011 January import lpg 419
## 3 2011 January import ms 20
## 4 2011 January import naphtha 153
## 5 2011 January import atf 0
## 6 2011 January import sko 129
## 7 2011 January import hsd 508
## 8 2011 January import ldo 0
## 9 2011 January import lobs_lube_oil 116
## 10 2011 January import fuel_oil 95
## # ℹ 1,862 more rows
dout <- data_to_hierarchical(t, c(year, Product, months), Quantity)
hchart(dout, type="sunburst")